Table REF  shows the average planning and execution time for each module discussed in Section . We increase the number of objects on the table and for each object number, we perform the experiment 3 times by randomly sampling the target location. Table REF  reports the average network depth \(d\) , average total task planning time, average total motion planning time, average number of motion planning attempts and the average number of objects to be re-arranged. Task planning times with increasing network depth corroborates our discussion on time complexity (see Section ) and is almost linear with respect to \(d\) . For motion planning, we use Moveit package [1]} as RRT planner within OMPL [2]} and we place a time bound of one second. However, motion planning failures due to actuation errors, grasping failures or occlusion lead to re-plan, explaining the large number of motion planning attempts.
